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lsantos7654/hivemind

Agent catalog manager for opencode — curates a shared catalog of domain-expert and team-lead agents, keeps deployed agent files in sync, and provides a TUI dashboard for managing the full agent lifecycle.

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README

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Agent catalog manager for OpenCode — clone repos, run AI-powered analysis, deploy expert subagents with structured knowledge docs and a shared memory system. The built-in librarian knows every expert so the assistant always knows who to ask.

License: MIT Python 3.12+

Quick Start

hivemind expert add https://github.com/koajs/koa  # clone + analyze → enabled

That's it. The expert is analyzed, deployed, and ready — spawn it with Task(subagent_type="expert-koa", ...).

Install

Requires only bazelisk. The Python toolchain, PyPI deps, bun, and the patched opencode engine are all built hermetically.

git clone https://github.com/lsantos7654/hivemind.git
cd hivemind
make install     # builds CLI + engine, symlinks ~/.local/bin/hivemind
hivemind sync    # bootstraps workspace — first run prompts for model config

The first time you run hivemind sync, it will prompt you to pick a default model and a small model from the available providers. If only OpenCode free models appear, authenticate first:

hivemind -- auth login
hivemind sync

Model selections are saved to config.json. After the prompt, re-run hivemind sync to complete workspace setup.

To bypass hivemind and access opencode directly, pass flags after --:

hivemind -- --help
hivemind -- -s ses_xxx          # resume a session
hivemind -- models              # list available models

Make sure ~/.local/bin is on your PATH. Python edits in src/hivemind/*.py are live without rebuild.

Command What it does
make install First-time: build CLI + engine, symlink launcher
make update After git pull or engine version bump
make test Full suite: unit + lint + typecheck + engine smoke
make clean bazel clean + remove launcher symlink

Commands

hivemind expert add <url> [--ref <ref>]        # clone + analyze, enabled by default
hivemind expert update <name>                   # fetch latest commit, re-analyze
hivemind expert switch-version <name> <ref>     # pin to tag/branch/commit
hivemind expert enable <name>                   # deploy agent file + symlink repo
hivemind expert disable <name>                  # remove agent file, keep data
hivemind expert delete <name> [--purge-memory]
hivemind expert list                            # table: name, status, HEAD, remote
hivemind expert show <name>                     # detail panel
hivemind expert crawl <url> <agent> [--max-pages N]

Two lifecycle states:

State Meaning
enabled Deployed as a subagent, repo cloned + symlinked
disabled Undeployed, backing data preserved

Teams

hivemind team create <name> -d <description> -e <expert,...>
hivemind team list
hivemind team show <name>
hivemind team add-expert <team> <expert,...>
hivemind team remove-expert <team> <expert>
hivemind team delete <team> [--force]
hivemind team enable <name>
hivemind team disable <name>

Team leads route questions to roster members by reading each expert's memory tree. Creating a team lands as enabled; roster mutations are fast (no curator needed).

Server

hivemind server start [--port N] [--hostname H]
hivemind server stop
hivemind server status

Server mode keeps the engine alive as a background process. Benefits: MCP subprocess survives session close, agent validation is cached once, multiple TUI sessions share the same session tree, catalog mutations reload agents without tearing down your conversation.

System

hivemind status               # engine, model, server, expert/team counts
hivemind sync                   # sync workspace: deploy agents, sweep stale files, regenerate librarian
hivemind tui                   # Textual-based TUI dashboard (Experts / Teams tabs)
hivemind mcp                   # MCP server (stdio transport)
hivemind                       # launch opencode (attaches to server if running)
hivemind -- -s ses_xxx         # forward args to opencode (-- separator required)

How It Works

Expert Structure

Each expert is a versioned directory with AI-generated knowledge docs:

experts/
  koa/
    HEAD -> a3930898ad18/          # symlink to active version
    a3930898ad18/
      agent.md                     # expert prompt body
      summary.md                   # repository overview
      code_structure.md            # annotated directory tree
      build_system.md              # build tooling and dependencies
      apis_and_interfaces.md       # public APIs and usage patterns
      description.md               # hand-editable summary (preserved across updates)
      expertise.md                 # hand-editable expertise claims (preserved across updates)

description.md and expertise.md are preserved across updates — the curator regenerates the other four files.

Deployed Layout

~/.config/opencode/
  agents/
    expert-koa.md               # expert agent
    team-lead-hivemind.md       # team lead agent
    librarian.md                # auto-generated catalog
  experts/                      # symlinks to ~/.cache/hivemind/experts/
  commands/                     # symlinked from opencode/commands/
  skills/                       # symlinked from opencode/skills/
  hivemind/memory/<name>/       # per-agent memory tree

~/.cache/hivemind/
  repos/koa/                    # cloned repository
  external_docs/koa/            # crawled documentation (optional)
  experts/koa/<commit>/         # analysis doc versions
  server.json / server.log      # server lifecycle state

Teams

Teams group experts under a team lead (roster_templated kind). The lead's prompt is assembled from a Jinja2 template plus one section per roster member:

teams/
  hivemind/
    expert-bazel.md             # per-expert routing reference
    expert-rich.md              # ...
    description.md              # team description
    lead.md                     # generated team-lead prompt
    notes.md                    # team-lead's self-managed notes

Per-expert sections are written by hivemind-expert-curator during team creation.

The Librarian

librarian.md knows every enabled expert and team. Regenerated automatically on enable, disable, delete, and redeploy. Spawn it with Task(subagent_type="librarian", ...).

Memory System

Each enabled agent owns a durable memory tree at ~/.config/opencode/hivemind/memory/<name>/:

short_memory.md    # working context — appended to on every reply
long_memory.md     # consolidated knowledge promoted by the daemon
<topic>.md         # topic files (daemon-created)

Compaction: hivemind-memory-daemon auto-promotes entries from short_memory.md to long_memory.md (or new topic files) when the byte threshold is crossed. Triggered by the file-write hook — never invoked manually.

The orchestrator (your main session) writes to ~/.config/opencode/hivemind/memory/_orchestrator/.

Configuration

Two config files in the repo root:

File Tracked? Purpose
hivemind.json Yes Engine settings + agent catalog (shared)
config.json No Per-machine model selection + enabled/disabled agent names

After editing hivemind.json, run hivemind sync.

External Documentation

hivemind expert crawl https://docs.example.com my-expert

Probes the site, picks sitemap / spider / Playwright, and saves clean markdown to ~/.cache/hivemind/external_docs/<agent>/. Experts read from that path natively. JS-rendered sites need Chromium — run uv run playwright install chromium once.

Shell Completion

hivemind --install-completion

All commands support tab completion for expert and team names.

Requirements

  • bazelisk on your PATH
  • ~/.local/bin on your PATH

Contributors

lsantos7654

Issues